Description

You will use Python and statistical analysis to uncover insights from consumer credit data, helping financial institutions predict behavior and assess risk.

This role is on-site.

Responsibilities

• Collect, clean, and analyze large datasets of consumer credit report information.
• Develop custom Python scripts, models, and algorithms to identify relationships between credit data and negative behaviors like loan defaults.
• Perform statistical analysis to quantify correlation strength and assess significance.
• Build interactive data visualizations to communicate findings to business stakeholders.
• Document analytical methodologies and collaborate with cross-functional teams to implement data-driven strategies.

Required Skills

• 3+ years of experience in data analysis, data modeling, and software development using Python.
• Strong proficiency in Python, including NumPy, Pandas, Matplotlib, and Scikit-learn.
• Bachelor's degree in Computer Science, data science, statistics, or a related quantitative field.
• Familiarity with consumer credit reporting data and creditworthiness factors.
• Ability to work independently and within collaborative teams.
• Strong problem-solving, critical thinking, and communication skills.

Preferred Skills

• Experience with SQL, Spark, or other big data technologies.
• Knowledge of machine learning techniques and their business applications.
• Understanding of consumer finance regulations and industry best practices.

Key Skills

Education

Bachelor's degree in Computer Science